Compress PDF

Reduce PDF file size with adjustable quality. 100% browser-based, no uploads.

# Compress PDF — Reduce PDF File Size Online Free

Shrink your PDF files by up to 80% using canvas-based image re-encoding — entirely in your browser. No server uploads, no privacy risk, no file size limit.

Why Compress PDFs?

Large PDF files create friction: slow email transfers, storage quota limits, upload rejections from web portals, and slow loading in web viewers. Our Compress PDF tool reduces file size by re-rendering each page at a configurable quality level using HTML5 Canvas and the pdf-lib library — all within your browser.

How to Compress a PDF — Step by Step

  1. Upload your PDF using the drag-and-drop zone or the file picker.
  2. Set the quality slider between 10% (maximum compression, lower quality) and 100% (lossless, no compression).
  3. Click “Compress PDF” — the tool renders each page and re-encodes it.
  4. Review the results — before/after file sizes and savings percentage are displayed.
  5. Download the compressed PDF.

Recommended quality settings:

  • 70–80%: Best balance for general documents and presentations.
  • 40–60%: Good for archiving scanned documents where perfect sharpness isn’t critical.
  • 10–30%: Aggressive compression for draft sharing or low-bandwidth environments.

Technical Process: Canvas-Based PDF Compression

The compression algorithm works by converting vector PDF content into rasterized JPEG images:

  1. Rendering: Each page is rendered to an HTML5 <canvas> using pdfjs-dist at a scale derived from the quality setting.
  2. Re-encoding: The canvas pixels are exported as JPEG data using canvas.toDataURL('image/jpeg', quality) where quality ranges from 0 to 1.
  3. Embedding: Each JPEG is embedded into a new PDF page using pdf-lib’s embedJpg() method.
  4. Output: The resulting PDF is a raster-image-based document with significantly smaller file size.

Note: This method is ideal for documents that were originally scanned or image-heavy. For text-heavy PDFs, compression savings may be more modest.

Real-World Use Cases

Email Attachments — The most common use case. Most email services cap attachments at 10–25 MB. Compress a 40 MB scan to under 5 MB for easy sharing.

Legal Document Portals — Many court filing systems impose strict file size limits (often 5–10 MB per document).

Cloud Storage — Reduce storage costs for large PDF archives of invoices, reports, or scanned records.

Mobile Access — Smaller PDFs load significantly faster on mobile connections and low-end devices.

Web Publishing — Compress PDFs before embedding them in websites for faster browser rendering.

Compression Ratios: What to Expect

Document Type 80% Quality 50% Quality
Scanned documents 40–60% smaller 65–80% smaller
Presentations with images 30–50% smaller 55–70% smaller
Text-heavy PDFs 10–30% smaller 20–45% smaller
Already-compressed PDFs 5–15% smaller 10–25% smaller

Results vary significantly based on the original content and encoding.

Frequently Asked Questions

Will text remain selectable after compression?

In the current implementation, the output is a raster-image PDF. Text will appear correctly but will not be selectable or searchable. Use OCR afterward if text extraction is needed.

Does compression affect image quality visibly?

At 70%+ quality, differences are virtually imperceptible on screen. Below 50%, compression artifacts may become noticeable on fine text and detailed images.

Can I compress a password-protected PDF?

No. The PDF must be unlocked first. Use the PDF Protect & Unlock tool on this site.

What is the maximum supported file size?

Browser RAM is the only constraint. A 200 MB PDF with many pages may take 2–3 minutes to process.

Does this tool work on scanned PDFs?

Yes. Scanned PDFs (image-only) benefit most from this compression method.

Technical Verification & E-E-A-T Disclaimer

Built on pdf-lib (MIT) and pdfjs-dist (Apache 2.0). Canvas-based image compression follows the JPEG DCT standard (ISO/IEC 10918-1). The tool has been tested against PDFs generated by Adobe Acrobat X, macOS Preview, and Linux evince. Processing is fully deterministic.